Senior Machine Learning Software Engineer (Match Group AI)

• Lead Projects Across Teams: Turn a broad goal into a concrete plan, and keep ML Engineers, PMs, and brand partners across our global offices (Palo Alto, LA, New York, Vancouver, Dallas, Tokyo) aligned. Clear blockers, including ones outside our team.
• Design and Build ML Systems: Design backend services and real-time/batch data pipelines that bring ML models to production, from first prototype to millions of users. Work as a real technical partner to ML Engineers.
• Serve Models Fast and at Low Cost: Serve deep learning models and large language models with low latency and reasonable GPU cost. Improve throughput with batching, caching, and better use of hardware.
• Raise the Bar: Set the example in problem definition, design docs, and AI-driven development, and help other engineers grow.

• Project Ownership (most important): A track record of leading a complex project from a rough goal to a production system you could stand behind: defining the problem, choosing the technical direction, and owning the outcome. You can explain the trade-offs behind your technical and product decisions.
• Engineering Experience: 5+ years of software engineering (backend, ML systems, data engineering, or similar), including building and running services or data pipelines in production.
• System Design: You can design scalable, reliable systems and clearly explain the trade-offs.
• Hands-on Coding With AI: You write clean, well-tested code (Python preferred), and AI coding agents are part of your daily work.
• High Agency and Grit: You find what needs to be done and drive it to a result fast, without waiting for instructions or cutting corners on quality. When you hit a wall, you find another way.
• Collaborative and Coachable: You understand what others really need and can persuade them. You take feedback well, act on it, and use AI to learn new things quickly.
• Professional Working Proficiency in English and Korean: Able to lead business meetings and take part in complex discussions without help.

• Have a strong base in CS fundamentals, or have worked closely with ML Engineers on how models are trained and served
• Have worked as a tech lead or manager
• Have built Trust & Safety systems, recommendation system, AI product features, or ML APIs used by multiple teams
• Have served ML models (vLLM, Triton, Ray Serve) or built large-scale backends and data pipelines (Spark, Flink, Kafka)
• Have turned vague product ideas into something users love, without every detail spelled out
• Have worked with teams in other companies, countries, or time zones
• Native-level English

• On-device AI Face Verification Pipeline Optimization
• 10 Python Performance Optimization Tips for High-Performance ML Backends

• Work type: Full-time
• Legal Entity: Hyperconnect / Brand: Match Group AI
• Recruitment Process: Resume Review > Technical Interview > Technical Deep-dive & Cultural Alignment Interview > Offer
• (* Please note that part of the interview process may be conducted in English)
• For the document screening stage, only successful candidates will be individually notified of the results.
• Application documents: A detailed, career-based English resume (PDF) in free format

#mg

#LI-YN1